1 / 22

Verifying Data Structure Invariants in Device Drivers

Verifying Data Structure Invariants in Device Drivers. Scott McPeak (smcpeak@cs) George Necula (necula@cs). Motivation. Want to verify programs that use pointers Need precise description of heap’s shape Traditional alias analysis won’t do

Download Presentation

Verifying Data Structure Invariants in Device Drivers

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Verifying Data Structure Invariantsin Device Drivers Scott McPeak (smcpeak@cs)George Necula (necula@cs)

  2. Motivation • Want to verify programs that use pointers • Need precise description of heap’s shape • Traditional alias analysis won’t do • Must be able to do strong updates, i.e. distinguish a particular object from the rest • Examples • “This is a tree” • “These structures are disjoint” • “Node p is reachable from node q” • BUT: Language should be simple, tractable • Our approach: FODIL, a First-Order Data structure Invariant Language

  3. The FODIL Language Invariant Quantifier Predicate Atom Term

  4. Full FODIL is undecidable • Problem: lots of function symbols • e.g., can reduce word problem: • given abc=def, de=s, sf=q, cba=q • is abc=cba ? • yes: abc ! def ! sf ! q ! cba • to FODIL: • 8 p. p->a->b->c = p->d->e->f,8 p. p->d->e = p->s,8 p. p->s->f = p->q • is x->a->b->c = x->c->b->a ?

  5. Ghost fields • Verifier treats them like other fields • Added to assist description • Way of making global properties local • Like strengthening an inductive hypothesis • Must be updated like other fields! • For now, this is done manually • But like other annotations, inference is possible • Compiler ignores them • Hence, can’t be inspected at run-time • Discarding ghost fields can be seen as an optimization

  6. Injectivity Pattern • Want to say: “these nodes form a tree” struct Node { Node *left; Node *right; };

  7. Injectivity Pattern • Want to say: “these nodes form a tree” • Instead #1: “the child selector is injective” struct Node { Node *left; Node *right; }; p->left child(p, “left”) p->right child(p, “right”)

  8. Injectivity Pattern • Want to say: “these nodes form a tree” • Instead #1: “the child selector is injective” • Instead #2: “child selector has an inverse” struct Node { Node *left; Node *right; Node *parent; bool isLeft; }; p->left child(p, true) p->right child(p, false) p->parent fst(child-1(p)) p->isLeft snd(child-1(p)) 8 p. p->left->isLeft == true && p->left->parent == p;

  9. Transitivity Pattern • Want to say that all reachable nodes have some property • Instead, associate the property with a ghost field • Then say neighbor nodes’ fields are equal struct Node { Node *next; Node *head; }; 8 p. p->next->head == p->head;

  10. Dynamic types • Every static type has a corresponding dynamic type tag • Every structure has a (ghost) tag field • malloc sets the tag to the proper value • free sets the tag to zero • An object must have the proper tag for a field access to be safe (i.e. not a dangling reference) • NULL’s tag is zero, so a nonzero tag implies a pointer is not NULL

  11. head ... M M ... Example: Linked list of circular lists backbone rings

  12. head ... M M ... Example: Linked list of circular lists struct BNode { BNode *next; BNode *prev; RNode *ring; }; struct RNode { BNode *bnode; RNode *next; RNode *prev; };

  13. Example: Linked list of circular lists forall(BNode *b) { b->next != NULL ==> b->next->prev == b; b->ring->tag == RNode; b->ring->bnode == b; } forall(RNode *r) { r->next->tag == RNode; r->prev->tag == RNode; r->next->prev == r; r->prev->next == r; r->next->bnode == r->bnode; }; struct BNode { BNode *next; BNode *prev; RNode *ring; }; struct RNode { BNode *bnode; RNode *next; RNode *prev; }; inj inj inj inj trans

  14. Verification: deallocNode() deallocNode(...) { for (BNode *b = head; b; b = b->next) { if (...) { RNode *r = b->ring; do { if (... && r != r->next) { // remove ‘r’ from its ring r->prev->next = r->next; r->next->prev = r->prev; if (r->bnode == b) b->ring = r->next; free(r); return; } r = r->next; } while (r != b->ring); }}}

  15. Proof: No dangling references Given: invariant held to begin with; r->bnode = b; b->ring ¹ r; r->tag = 0; Goal: 8 b. b->ring->tag = RNode :Goal, instantiated with fresh var: c->ring->tag ¹ RNode i.e. c->ring->(tag0{r a 0}) ¹ RNode forall(BNode *b) { ... b->ring->tag == RNode; b->ring->bnode == b; } If c->ring = r: then r->bnode = c so b = c, contr. If c->ring ¹ r: then c->ring->tag0¹ RNode contradicts orig. invariant

  16. Decision procedure • Key question: when to instantiate universally quantified facts? • Our answer (for now): ad-hoc matching • 8 p. p->a->b = p, match on “p->a” • 8 p. p->a->b = p->b, match on “p->a” or “p->b” • For these cases we can prove completeness • Relies on detailed reasoning about the e-dag, a data structure used by the theorem prover • Open question: more general strategy? • Have explored variation of Knuth-Bendix completion, still unclear if it can work

  17. Experimental Results • Verified two linux drivers (~1kloc each) • scull: Rubini example, complicated data str. • pc_keyb: PC keyboard + mouse driver • Verified several data structure kernels • lists, arrays, etc. • red-black trees • b+-trees (including balance + key properties) • Annotation effort metrics • Between 50 and 100% of original code size • Takes time to learn how the code works

  18. Related: Shape Types • Fradet and Métayer POPL97 • Formalism using graph grammars • Doubly-linked list: • Doubly ::= head x, pred x NULL, L xL x ::= next x y, pred y x, L y | next x NULL • Undecidable in general (like FODIL); but practical decidable subset not apparent • Arguably less natural ... • All examples in their paper are expressible in FODIL (with inj+trans only)

  19. Related: Graph Types • Moller and Schwartzbach PLDI01,Klarlund and Schwartzbach POPL93 • Invariants expressed as quantified formulas • Notion of trees is built into their logic; i.e. injectivity is implicit (no circular lists..) • Uses regular expressions to describe non-tree pointers’ targets • We can reduce deterministic graph types to FODIL (with inj+trans only)

  20. Related: 3-Valued Logic (TVLA) • (e.g.) Sagiv et. al TOPLAS02 • Abstract interpretation; heap abstraction has yes/no/maybe pointers (“3-Valued”) • Requires instrumentation predicates • Supplied by programmer, defined in terms of other fields, predicates • Many similarities to global invariants of ghost fields • Approach favors automation over precision • Not obvious how to extend (e.g. to specify a tree is balanced)

  21. Future Work • Generalize decidable FODIL forms • More atomic predicates: partial orders, ... • Change isolation; some connections to bunched implication • e.g.: ok for module A to call into module B while A’s invariant is broken, if B can’t see it • Annotation automation/inference • Existing invariant inference is simple, effective • Want annotation abstractions: “this kind of loop always has these invariants: ...” • More sophisticated proof failure diagnosis

  22. Conclusion • Device drivers use the heap nontrivially; must characterize that use precisely • Injectivity and transitivity are key concepts in data structure description • We can describe them using simple quantified equalities • No need to add trees or transitive closure to the logic • Ghost fields are a more tractable alternative, making global properties expressible locally

More Related